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authorS. Solomon Darnell2025-03-28 21:52:21 -0500
committerS. Solomon Darnell2025-03-28 21:52:21 -0500
commit4a52a71956a8d46fcb7294ac71734504bb09bcc2 (patch)
treeee3dc5af3b6313e921cd920906356f5d4febc4ed /.venv/lib/python3.12/site-packages/PIL/ImageChops.py
parentcc961e04ba734dd72309fb548a2f97d67d578813 (diff)
downloadgn-ai-4a52a71956a8d46fcb7294ac71734504bb09bcc2.tar.gz
two version of R2R are here HEAD master
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+#
+# The Python Imaging Library.
+# $Id$
+#
+# standard channel operations
+#
+# History:
+# 1996-03-24 fl   Created
+# 1996-08-13 fl   Added logical operations (for "1" images)
+# 2000-10-12 fl   Added offset method (from Image.py)
+#
+# Copyright (c) 1997-2000 by Secret Labs AB
+# Copyright (c) 1996-2000 by Fredrik Lundh
+#
+# See the README file for information on usage and redistribution.
+#
+
+from __future__ import annotations
+
+from . import Image
+
+
+def constant(image: Image.Image, value: int) -> Image.Image:
+    """Fill a channel with a given gray level.
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    return Image.new("L", image.size, value)
+
+
+def duplicate(image: Image.Image) -> Image.Image:
+    """Copy a channel. Alias for :py:meth:`PIL.Image.Image.copy`.
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    return image.copy()
+
+
+def invert(image: Image.Image) -> Image.Image:
+    """
+    Invert an image (channel). ::
+
+        out = MAX - image
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image.load()
+    return image._new(image.im.chop_invert())
+
+
+def lighter(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """
+    Compares the two images, pixel by pixel, and returns a new image containing
+    the lighter values. ::
+
+        out = max(image1, image2)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_lighter(image2.im))
+
+
+def darker(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """
+    Compares the two images, pixel by pixel, and returns a new image containing
+    the darker values. ::
+
+        out = min(image1, image2)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_darker(image2.im))
+
+
+def difference(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """
+    Returns the absolute value of the pixel-by-pixel difference between the two
+    images. ::
+
+        out = abs(image1 - image2)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_difference(image2.im))
+
+
+def multiply(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """
+    Superimposes two images on top of each other.
+
+    If you multiply an image with a solid black image, the result is black. If
+    you multiply with a solid white image, the image is unaffected. ::
+
+        out = image1 * image2 / MAX
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_multiply(image2.im))
+
+
+def screen(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """
+    Superimposes two inverted images on top of each other. ::
+
+        out = MAX - ((MAX - image1) * (MAX - image2) / MAX)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_screen(image2.im))
+
+
+def soft_light(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """
+    Superimposes two images on top of each other using the Soft Light algorithm
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_soft_light(image2.im))
+
+
+def hard_light(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """
+    Superimposes two images on top of each other using the Hard Light algorithm
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_hard_light(image2.im))
+
+
+def overlay(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """
+    Superimposes two images on top of each other using the Overlay algorithm
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_overlay(image2.im))
+
+
+def add(
+    image1: Image.Image, image2: Image.Image, scale: float = 1.0, offset: float = 0
+) -> Image.Image:
+    """
+    Adds two images, dividing the result by scale and adding the
+    offset. If omitted, scale defaults to 1.0, and offset to 0.0. ::
+
+        out = ((image1 + image2) / scale + offset)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_add(image2.im, scale, offset))
+
+
+def subtract(
+    image1: Image.Image, image2: Image.Image, scale: float = 1.0, offset: float = 0
+) -> Image.Image:
+    """
+    Subtracts two images, dividing the result by scale and adding the offset.
+    If omitted, scale defaults to 1.0, and offset to 0.0. ::
+
+        out = ((image1 - image2) / scale + offset)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_subtract(image2.im, scale, offset))
+
+
+def add_modulo(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """Add two images, without clipping the result. ::
+
+        out = ((image1 + image2) % MAX)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_add_modulo(image2.im))
+
+
+def subtract_modulo(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """Subtract two images, without clipping the result. ::
+
+        out = ((image1 - image2) % MAX)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_subtract_modulo(image2.im))
+
+
+def logical_and(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """Logical AND between two images.
+
+    Both of the images must have mode "1". If you would like to perform a
+    logical AND on an image with a mode other than "1", try
+    :py:meth:`~PIL.ImageChops.multiply` instead, using a black-and-white mask
+    as the second image. ::
+
+        out = ((image1 and image2) % MAX)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_and(image2.im))
+
+
+def logical_or(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """Logical OR between two images.
+
+    Both of the images must have mode "1". ::
+
+        out = ((image1 or image2) % MAX)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_or(image2.im))
+
+
+def logical_xor(image1: Image.Image, image2: Image.Image) -> Image.Image:
+    """Logical XOR between two images.
+
+    Both of the images must have mode "1". ::
+
+        out = ((bool(image1) != bool(image2)) % MAX)
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    image1.load()
+    image2.load()
+    return image1._new(image1.im.chop_xor(image2.im))
+
+
+def blend(image1: Image.Image, image2: Image.Image, alpha: float) -> Image.Image:
+    """Blend images using constant transparency weight. Alias for
+    :py:func:`PIL.Image.blend`.
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    return Image.blend(image1, image2, alpha)
+
+
+def composite(
+    image1: Image.Image, image2: Image.Image, mask: Image.Image
+) -> Image.Image:
+    """Create composite using transparency mask. Alias for
+    :py:func:`PIL.Image.composite`.
+
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    return Image.composite(image1, image2, mask)
+
+
+def offset(image: Image.Image, xoffset: int, yoffset: int | None = None) -> Image.Image:
+    """Returns a copy of the image where data has been offset by the given
+    distances. Data wraps around the edges. If ``yoffset`` is omitted, it
+    is assumed to be equal to ``xoffset``.
+
+    :param image: Input image.
+    :param xoffset: The horizontal distance.
+    :param yoffset: The vertical distance.  If omitted, both
+        distances are set to the same value.
+    :rtype: :py:class:`~PIL.Image.Image`
+    """
+
+    if yoffset is None:
+        yoffset = xoffset
+    image.load()
+    return image._new(image.im.offset(xoffset, yoffset))